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A hybrid model for capturing implicit spatial knowledge

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Published
Publication date09/2005
Host publicationTAMODIA '05 Proceedings of the 4th international workshop on Task models and diagrams
Place of PublicationNew York
PublisherACM
Pages49-54
Number of pages6
ISBN (print)1595932208
<mark>Original language</mark>English
Event4th International Workshop on TAsk MOdels and DIAgrams for User Interface Design for Work and Beyond -
Duration: 1/01/1900 → …

Conference

Conference4th International Workshop on TAsk MOdels and DIAgrams for User Interface Design for Work and Beyond
Period1/01/00 → …

Conference

Conference4th International Workshop on TAsk MOdels and DIAgrams for User Interface Design for Work and Beyond
Period1/01/00 → …

Abstract

This paper proposes a machine learning-based approach for capturing rules embedded in users’ movement paths while navigating in Virtual Environments (VEs). It is argued that this methodology and the set of navigational rules which it provides should be regarded as a starting point for designing adaptive VEs able to provide navigation support. This is a major contribution of this work, given that the up-to-date adaptivity for navigable VEs has been primarily delivered through the manipulation of navigational cues with little reference to the user model of navigation.